The goal of using an automated image identification system to recognize road signs and traffic signs is well known. Various techniques have been proposed for the recognition of road signs as part of a real-time automated vehicle navigation system. Due to the processing limitations imposed by a real-time environment, almost all of these techniques have involved template matching of shape and color. Given the wide variations in lighting and conditions, few if any of these systems provide accurate results.
Another use of automated road sign recognition is for the purpose of identifying and creating an accurate inventory of all road signs and traffic signs along a given street or highway. In one system as described in U.S. Pat. No. 6,266,442, entitled, issued Jul. 24, 2001, to Laumeyer et al., an acquisition vehicle equipped with video cameras and position identifying technology, such as global positioning satellite (GPS) receivers, is systematically driven over the roads and streets in a given area to produce a videostream tagged with location information. The tagged videostream is analyzed by computer software routines to perform object recognition of the desired objects, the road signs in this case. The results of this analysis are exported to an asset management database that stores attributes of the road signs.
Road signs are manufactured from a sheeting material made up of multiple layered films (one or more colored layers that are fused with a layer that produces the reflectivity) that is adhered to the sign face. There are different types of sheeting material utilized in the road sign industry. Currently, specific attributes about each road sign like retroreflectivity (measured in candelas/lux/sq. meter) and sheeting type must be gathered manually by sending personnel in the field to measure retroreflectivity with a handheld device (like the Impulse RM retro-reflectometer from Laser Technology, Inc.) and to visually determine the sheeting type of each sign. Measurements of retroreflectivity and identification of sheeting type are helpful in evaluating the visibility of a sign and whether it has deteriorated due to a breakdown in the pigments or reflective material in the sheeting material of the sign. The retroreflectivity and sheeting type can also be used to produce a predictive model of how the sign will perform into the future based on the as-measured characteristics.
Generally, highway and street maintenance departments do not systematically evaluate the deterioration of the reflective materials used on road signs and markers. If inspections of road signs or markers are performed, they are typically accomplished by having inspectors manually position a handheld retroreflectometer directly on the surface of a sign in order to determine a retroreflectivity value for that sign. When there are a large number of road signs or markers (sometimes referred to as traffic control devices or TCDs) in a given jurisdiction, the task of manually inspecting all of these road signs and markers can be time consuming and expensive.
One technique for determining retroreflectivity, designated as “RA” generally (and from time to time in this disclosure), which does not require that a retroreflectometer be placed directly on a sign is described in U.S. Pat. No. 6,212,480 entitled, issued Apr. 3, 2001, to Dunne. The Dunne patent relates to a device commercialized by the assignee thereof and marketed as the “Impulse RM” retro-reflectometer by Laser Technology, Inc., of Englewood, Colo., USA. In use, handheld devices fabricated according to the Dunne patent are manually directed toward, or precisely at, a target object and then manually “fired.” Once fired, the handheld device bounces a laser off the target object and measures the reflected laser energy that is then used to determine a retroreflectivity.
There are several drawbacks of the handheld laser arrangement described by the Dunne patent. The handheld device can only measure a single color at a time and can only measure one object at a time. The determination of retroreflectivity for a given object is valid only for the actual location, or discrete measurement point, along the roadway at which the measurement was made by the human operator. In order to validate a measurement made by such devices, the device must be taken back to the precise location in the field where an original measurement occurred for a valid comparison measurement to be made.
Another technique established for determining the retroreflectivity of signs has been introduced by the Federal Highway Administration (FHWA). The Sign Management and Retroreflectivity Tracking System (SMARTS) is a vehicle that contains one high intensity flash source (similar to the Honeywell StrobeGuard™ SG-60 device), one color camera, two black and white cameras, and a range-sensing device. The SMARTS vehicle requires two people for proper operation—one driver and one system operator to point the device at the target sign and arm the system. The SMARTS travels down the road, and the system operator “locks on” to a sign up ahead by rotating the camera and light assembly to point at the sign. At a distance of 60 meters, the system triggers the flash source to illuminate the sign surface, an image of which is captured by one of the black and white cameras. A histogram is produced of the sign's legend and background that is then used to calculate retroreflectivity. A GPS system stores the location of the vehicle along with the calculated retroreflectivity in a computer database.
Like the handheld laser device of the Dunne patent, the SMARTS device can only determine retroreflectivity for one sign at a time and can only determine retroreflectivity for the discrete point on the roadway 60 meters from the sign. Two people are required to operate the vehicle and measurement system. The SMARTS vehicle cannot make retroreflectivity determinations for signs on both sides of the roadway in a single pass over the roadway, and does not produce nighttime sign visibility information for lanes on the roadway not traveled by the vehicle. Because the system operator in the SMARTS vehicle must locate and track signs to be measured while the vehicle is in motion, a high level of operational skill is required and the likelihood that a sign will be missed is significant. Most importantly for purposes of the present invention, the SMARTS device makes no attempt to automatically determine sheeting type of a sign.
There are an estimated 58 million individual TCDs that must be monitored and maintained in the United States and new TCD installations increase this number daily. For the reasons that have been described, the existing techniques for determining retroreflectivity do not lend themselves to increasing processing throughput so as to more easily manage the monitoring and maintenance of these TCDs. So called automated data collection systems often require that normal traffic be stopped during data collection because either the acquisition vehicle moved very slowly or because the acquisition vehicle had to come to a full stop before recording data about the roadside scene. Furthermore, a human operator is required to point one or more measurement devices at a sign of interest, perform data collection for that particular sign and then set up the device for another particular sign of interest. With such a large number of TCDs that must be monitored, it would be desirable to provide an automated system for determining the retroreflectivity of road signs and markers that addresses these and other shortcomings of the existing techniques to enable a higher processing throughput of an automated determination of the retroreflectivity and sheeting classification of road signs and markers.